You've deployed your Task API to a cloud Kubernetes cluster. But deployed doesn't mean production-ready. A deployment can run without being resilient, observable, or secure.
This chapter gives you a systematic approach: a 10-point production readiness checklist that separates "it works on my cluster" from "it's ready for real traffic."
The pattern you'll learn here applies to any Kubernetes deployment—not just DigitalOcean, not just Task API. Once you internalize this checklist, you can verify any deployment on any cloud.
Airplane pilots use pre-flight checklists despite thousands of hours of experience. Surgeons use surgical checklists despite years of training. The reason? Humans forget things under pressure, and production deployments happen under pressure.
A deployment might fail silently in ways that only manifest under load:
The checklist catches these issues before customers do.
Let's verify each item systematically.
The health endpoint is your deployment's vital sign. If it doesn't respond, nothing else matters.
Output (Pass):
Output (Fail):
A 000 response typically means DNS isn't resolving or the service isn't reachable. Check your Ingress and DNS configuration.
For more detail:
Output (Pass):
What you're verifying: The entire path works—DNS resolves, Load Balancer routes, Ingress matches, Service forwards, Pod responds.
Without resource limits, a single misbehaving pod can consume all node resources, crashing other workloads.
Output (Pass):
Output (Fail):
If you see <none>, add resource specifications to your deployment:
What you're verifying: Kubernetes knows how much CPU and memory your pods need, enabling proper scheduling and preventing resource starvation.
A single replica means zero redundancy. If that pod crashes or its node goes down, your service is unavailable.
Output (Pass):
Output (Fail):
Scale up if needed:
What you're verifying: Your service survives the loss of any single pod or node.
Liveness probes tell Kubernetes when to restart a stuck container. Without them, a deadlocked process runs forever.
Output (Pass):
Output (Fail):
If missing, add to your deployment spec:
What you're verifying: Kubernetes will automatically restart containers that become unresponsive.
Readiness probes tell Kubernetes when a pod is ready to receive traffic. Without them, traffic routes to pods still initializing.
Output (Pass):
What you're verifying: Traffic only routes to pods that are fully initialized and ready to handle requests.
HTTPS requires a valid, non-expired certificate. An invalid certificate breaks trust for browsers and API clients.
Output (Pass):
Output (Fail):
If using cert-manager, check certificate status:
Output:
What you're verifying: Your HTTPS endpoint is secure and trusted by clients.
Sensitive values should never appear in plain text when describing pods.
Output (Pass):
Output (Fail):
If secrets appear in plain text, refactor to use Kubernetes Secrets:
What you're verifying: Sensitive values aren't exposed in logs, kubectl output, or memory dumps.
PodDisruptionBudgets (PDBs) prevent Kubernetes from terminating too many pods during node maintenance.
Output (Pass):
Output (Fail):
Create a PDB if missing:
What you're verifying: Your service remains available during cluster upgrades and node maintenance.
HorizontalPodAutoscaler (HPA) scales pods based on CPU or memory usage.
Output (Pass):
Output (Fail for traffic-receiving services):
For services expecting variable traffic, create an HPA:
What you're verifying: Your service scales automatically under load instead of becoming unresponsive.
Production readiness includes knowing what you're paying.
Access your cloud provider's dashboard:
Document:
What you're verifying: No surprises on your cloud bill.
Output:
Check logs for the crash reason:
Output (Fail):
Fix by creating or updating image pull secret:
Here's a script that runs all checks:
Output:
Use your AI companion to verify your production deployment collaboratively.
What you're learning: Pattern recognition—AI helps you spot configuration gaps you might overlook and generates correct fixes faster than manual YAML writing.
What you're learning: Systematic debugging—AI helps you prioritize issues and identify root causes when multiple things fail simultaneously.
What you're learning: Checklist adaptation—production checklists should be customized for your application's specific dependencies and requirements.
Always run verification commands on your actual deployment, not just in theory. AI can generate perfect-looking commands, but only execution against real infrastructure confirms your deployment is truly production-ready.
Test your multi-cloud-deployer skill:
If gaps exist, update your skill with the 10-point checklist pattern and debugging procedures from this chapter. A deployment skill isn't complete without verification capability.